Many businesses collect large amounts of data about their customers. They are interested in finding the patterns of behavior in these datasets which will help them to understand their customers and which can be exploited in order to improve customer experience, inform business strategies or increase revenue.
In order make sense of such datasets, it is common to build statistical models or to perform statistical analyses. However these models are often hard to interpret, particularly for an audience with no specialist knowledge. Furthermore, it is often necessary to explore the model and the dataset with a specific hypothesis in mind in order to understand what has been learned. This is a laborious process and is limited by the extent of the initial hypotheses the user is able to imagine.